Changde Cheng Lab
Computational Biology and Cancer Genomics
We investigate the impact of (epi-)mutations and cell-cell communication in cancer genomics using computational and analytical methods. We develop innovative analytical methods and machine-learning tools to advance our understanding of cancer biology in patients. We take high-throughput approaches, including single-cell RNA-seq, spatial, multiomics, and perturbation sequencing, to study cancer’s origin, progression, and therapeutic resistance. Our research focuses on identifying the cancer cell subpopulations responsible for relapse and understanding how microenvironments influence their response to treatment by decoding communication networks among cells.
Our ultimate goal is to translate our research findings into clinical settings to improve cancer treatment precision, minimize disease recurrence risk, and enhance patient outcomes.
